Computer, enhence : POS-tagging improvements for nonbinary pronoun use in Swedish

• Part of Speech (POS) taggers for Swedish routinely fail for the third person gender-neutral pronoun hen, despite the fact that it has been a well-established part of the Swedish language since at least 2014. In addition to simply being a form of gender bias, this failure can have negative effects on other tasks relying on POS information. We demonstrate the usefulness of semi-synthetic augmented datasets in a case study, retraining a POS tagger to correctly recognize hen as a personal pronoun. We evaluate our retrained models for both tag accuracy and on a downstream task (dependency parsing) in a classicial NLP pipeline.Our results show that adding such data works to correct for the disparity in performance. The accuracy rate for identifying hen as a pronoun can be brought up to acceptable levels with only minor adjustments to the tagger’s vocabulary files. Performance parity to gendered pronouns can be reached after retraining with only a few hundred examples. This increase in POS tag accuracy also results in improvements for dependency parsing sentences containing hen.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Språkteknologi (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Language Technology (hsv//eng)

Nyckelord

Part-of-Speech

gendered pronouns

neopronouns

computational linguistics

datorlingvistik

Publikations- och innehållstyp

ref (ämneskategori)

kon (ämneskategori)